Python库 | gdxpds-1.0.3.tar.gz

gdx-pandas ========== Python package to translate between gdx (GAMS data) and pandas. [Install](#install) | [Use](#use) | [Uninstall](#uninstall) ## Use There are two main ways to use gdxpds. The first use case is the one that was initially supported: direct conversion between GDX files on disk and pandas DataFrames or a csv version thereof. The Version 1.0.0 rewrite intoduces a second style of use, that is, interfacing with GDX files and symbols via the `gdxpds.gdx.GdxFile` and `gdxpds.gdx.GdxSymbol` classes. [Direct Conversion](#direct-conversion) | [Backend Classes](#backend-classes) ### Direct Conversion The two primary points of reference for the direct conversion utilities are GDX files on disk and python dicts of {symbol_name: pandas.DataFrame}, where each pandas.DataFrame contains data for a single set, parameter, equation, or variable. For sets and parameters, the last column of the DataFrame is assumed to contain the value of the element, which for sets should be `True`, and for parameters should be a `float` (or one of the `gdxpds.gdx.NUMPY_SPECIAL_VALUES`). Equations and variables have additional 'value' columns, in particular a level, a marginal value, a lower bound, an upper bound, and a scale, as enumerated in `gdxpds.gdx.GamsValueType`. These values are all assumed to be found in the last five columns of the DataFrame, also see `gdxpds.gdx.GAMS_VALUE_COLS_MAP`. The basic interface to convert from GDX to DataFrames is: ```python import gdxpds gdx_file = 'C:\path_to_my_gdx\data.gdx' dataframes = gdxpds.to_dataframes(gdx_file) for symbol_name, df in dataframes.items(): print("Doing work with {}.".format(symbol_name)) ``` And vice-versa: ```python import gdxpds # assume we have a DataFrame df with last column 'value' data_ready_for_GAMS = { 'symbol_name': df } gdx_file = 'C:\path_to_my_output_gdx\data_to_send_to_gams.gdx' gdx = gdxpds.to_gdx(data_ready_for_GAMS, gdx_file) ``` Note that providing a gdx_file is optional, and the returned gdx is an object of type `gdxpds.gdx.GdxFile`. Additional functions include: - `gdxpds.list_symbols` - `gdxpds.to_dataframe` (If the call to this method includes old_interface=False, then the return value will be a plain DataFrame, not a {'symbol_name': df} dict.) The package also includes command line utilities for converting between GDX and CSV, see ```bash python C:\your_python_path\Scripts\gdx_to_csv.py --help python C:\your_python_path\Scripts\csv_to_gdx.py --help ``` ### Backend Classes The basic functionalities described above can also be achieved with direct use of the backend classes now available in `gdxpds.gdx`. To duplicate the GDX read functionality shown above one would write: ```python import gdxpds gdx_file = 'C:\path_to_my_gdx\data.gdx' with gdxpds.gdx.GdxFile(lazy_load=False) as f: f.read(gdx_file) for symbol in f: symbol_name = symbol.name df = symbol.dataframe print("Doing work with {}:\n{}".format(symbol_name,df.head())) ``` The backend especially gives more control over creating new data in GDX format. For example: ```python import gdxpds out_file = 'my_new_gdx_data.gdx' with gdxpds.gdx.GdxFile() as gdx: # Create a new set with one dimension gdx.append(gdxpds.gdx.GdxSymbol('my_set',gdxpds.gdx.GamsDataType.Set,dims=['u'])) data = pds.DataFrame([['u' + str(i)] for i in range(1,11)]) data['Value'] = True gdx[-1].dataframe = data # Create a new parameter with one dimension gdx.append(gdxpds.gdx.GdxSymbol('my_parameter',gdxpds.gdx.GamsDataType.Parameter,dims=['u'])) data = pds.DataFrame([['u' + str(i), i*100] for i in range(1,11)], columns=(gdx[-1].dims + gdx[-1].value_col_names)) gdx[-1].dataframe = data gdx.write(out_file) ``` ## Install ### Preliminaries - Python 2.6 or higher 2.X; Python 3.4 or higher 3.X - pandas (In general you will want the SciPy stack. Anaconda comes with it, or see [my notes for Windows](http://elainethale.wordpress.com/programming-notes/python-environment-set-up/).) - For Python versions < 3.4, enum34. Also **uninstall the enum package** if it is installed. - psutil (optional--for monitoring memory use) - pytest (optional--for running tests) - GAMS Python bindings - See GAMS/win64/XX.X/apifiles/readme.txt on Windows, GAMS/gamsXX.X_osx_x64_64_sfx/apifiles/readme.txt on Mac, or /opt/gams/gamsXX.X_linux_x64_64_sfx/apifiles/readme.txt on Linux - Run the following for the correct version of the Python bindings ```bash python setup.py install ``` or ```bash python setup.py build --build-base=/path/to/somwhere/you/have/write/access install ``` with the latter being for the case when you can install packages into Python but don't have GAMS directory write access. - .../apifiles/Python/api/setup.py works for Python 2.7 - For other versions of Python, especially 3.X, use .../apifiles/Python/api_XX/setup.py. For Python 3.X in particular you will need GAMS version >= 24.5.1 (Python 3.4, Windows and Linux), 24.7.4 (Python 3.4, Mac OS X), or >= 24.8.4 (Python 3.6) ### Get the Latest Package ```bash pip install git+https://github.com/NREL/gdx-pandas.git@master ``` or ```bash pip install git+https://github.com/NREL/gdx-pandas.git@v1.0.3 ``` Versions are listed at https://github.com/NREL/gdx-pandas/releases. After installation, you can test the package using pytest: ```bash pytest --pyargs gdxpds ``` If the tests fail due to permission IOErrors, apply `chmod g+x` and `chmod a+x` to the `gdx-pandas/gdxpds/test` folder. ## Uninstall ``` pip uninstall gdxpds ```